{"url":"/dataset/rir-dataset","name":"RIR dataset","full_name":"Planar Room Impulse Response Dataset - ACT, DTU Electro (b. 355 r. 008)","description_markdown":"Dataset of Room Impulse Responses measured at the Acoustic Technology group facilities, DTU Electro. The measurements were carried out in building 355, room 008, otherwise known as the \"sound field control\" room.\r\n\r\nThe dataset consists of measurements of the acoustic impulse response in a regular square grid of 80x80 cm2. The measurements consist of 30x30 room impulse responses (e.g. 900 RIRs) where the microphone, a 1/2 inch free field condenser measurement microphone (Br\\\"uel\\&Kj\\\"aer, N\\ae rum, Denmark) was automatically positioned using a UR5 (Universal Robots, Odense, Denmark) scanning robotic arm. A BM6 loudspeaker (Dynaudio, Skanderborg, Denmark) placed in a room corner was used to excite the room with 5s wideband logarithmic sweeps.  \r\n\r\n\r\nThe data are available as H5 (Hierarchical Data Formats) with the following structure:\r\n\r\n\r\nDataset \"Sound field control room - HDF5 datastructure\"\r\n\r\nDataset.attributes\r\n   ├── calibration (1) '94.33 dB @ 1.14 kHz'\r\n   ├── fs (1) 48000 Hz\r\n   ├── grid_bottom (3x900) [[2.76, 2.32, 2.73, ...  2.738 2.76..., ...]] m\r\n   ├── loudspeaker_position (3) [5.779 0.263 0.904] m\r\n   ├── room_dimensions (3)  [6.124 5.771 3.073] m\r\n   ├── sweep_amplitude (1) 0.4\r\n   ├── sweep_duration (1) 5 s\r\n   ├── sweep_range (2) [32. 12000.] Hz\r\n   ├── temperature (1) 20.3 °C\r\n   └── true_calibration (1) '94.19 dB @ 1.17 kHz'\r\nDataset.groups\r\n   ├── Noise_recs_bottom (12x3x144000) float64\r\n   ├── RIRs_bottom (900x25439) float64 (e.g. 900 positions)\r\n   └── sweep_signal (288000) float64\r\n\r\nUse with Matlab: https://mathworks.com/help/matlab/hdf5-files.html \r\n\r\nUse with Python: https://docs.h5py.org/en/stable/","description_withheld":null,"homepage":"https://data.dtu.dk/articles/dataset/Planar_Room_Impulse_Response_Dataset_-_ACT_DTU_Electro_b_355_r_008_/21740453","introduced_date":"2024-01-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/room-impulse-response-reconstruction-with","title":"Room impulse response reconstruction with physics-informed deep learning","first_author":"Xenofon Karakonstantis","url":null},"license":{"name":"CC BY 4.0","url":null},"modalities":[{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["RIR dataset"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}